Site Reliability Engineer - Linux, Kubernetes, Terrraform

NO SPONSORSHIP - NO OPT

Site Reliability Engineering

This is all about Linux, Kubernetes, Docker, Terraform, Jenkins, Ansible, Harness

Observation, logging and Capacity planning

AI is a huge preference

Kafka is a huge preference, but not a must

SELLING POINTS: AWS Cloud application profiling monitoring logging metrics collection analysis AI ops splunk app dynamics data dog stack driver sys dig scripting bash python go messaging kafka rabbit mq active mq kubernetes docker swarm rancher Jenkins travis harness AI power tools linux

Qualifications:

• Experience with maintaining and troubleshooting large-scale distributed systems
• Experience with Agile / Scrum methodology
• Able to succeed in fast-paced environment with frequent changes

• Experience managing infrastructure in public cloud environments like AWS (preferred), Azure or Google Cloud Platform
• Experience with AIOps and predictive analysis for anomaly detection, forecasting system capacity using monitoring and alerting tools like Splunk, AppDynamics, Datadog, StackDriver, Sysdig, Prometheus or Grafana
• Programming/scripting experience in languages like Java, Bash, Python or Go
• Experience with Kafka, RabbitMQ, or ActiveMQ
• Experience with container orchestration systems like Kubernetes, Mesos, Docker Swarm or Rancher
• Experience with using Continuous Integration and Continuous Delivery (CI/CD) tools like Jenkins, Travis, Harness, Appveyor, CodeBuild or CodePipeline
• Familiarity with leveraging large language models (LLMs) to automate and optimize SRE workflows. This may include using AI-powered tools to perform tasks such as, writing scripts, summarizing incident reports, or even creating and maintaining AI workloads.
• Familiarity with leveraging large language models (LLMs) to automate and optimize SRE workflows. This may include using AI-powered tools to perform tasks such as, writing scripts, summarizing incident reports, data analysis or even creating and maintaining AI workloads.
• Basic exposure to Chaos Engineering tools like, Gremlin, Chaos Monkey, Harness Chaos Engineering, or cloud-native fault injection services like AWS FIS.
• Minimum of 4+ years of experience in Site Reliability Engineering / DevOps